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connection weights vs overall connection weights

Both phrases are correct, but they are used in slightly different contexts. 'Connection weights' refers to the individual weights assigned to connections in a network, while 'overall connection weights' refers to the collective sum or average of all connection weights in a network.

Last updated: March 17, 2024 • 944 views

connection weights

This phrase is correct and commonly used in the context of neural networks or machine learning to refer to the strength of connections between nodes.

This phrase is used to describe the individual weights assigned to connections between nodes in a network, such as in neural networks or machine learning models.

Examples:

  • The neural network adjusts the connection weights during training to improve performance.
  • The accuracy of the model depends on the optimal selection of connection weights.
  • Learning always involves modifying the connection weights. In general, these involve mathematical formulas to determine the change in weights when given ...
  • Connection weights (sometimes also called 'connection strengths') are positive or negative real numerical values. The amount of input a particular connection ...
  • Mar 1, 2011 ... I would guess that training tends to pulls a lot of connection weights down to zero (for non-informative features) and pushes a few away (for the ...
  • Interpreting neural-network connection weights, 1991 Article. Bibliometrics Data Bibliometrics. · Downloads (6 Weeks): n/a · Downloads (12 Months): n/a

Alternatives:

  • link weights
  • edge weights
  • synaptic weights
  • weight values
  • connection strengths

overall connection weights

This phrase is correct and is used to refer to the collective sum or average of all connection weights in a network.

This phrase is used when discussing the combined impact of all connection weights in a network, providing a holistic view of the network's connectivity.

Examples:

  • The overall connection weights determine the network's behavior.
  • By analyzing the overall connection weights, researchers can gain insights into the network's functioning.
  • tion test using relative importance (derived from. Garson's algorithm) differ from the results using overall connection weights. Using Garson's al- gorithm, surface  ...
  • i) overall connection weights method ii) Garson's method iii) The partial derivatives methods iv) The Input Perturb method v) the classical stepwise methods.
  • ABSTRACT With the growth of statistical modeling in the ecological sciences, researchers are using more complex methods, such as artificial neural networks  ...
  • Dec 21, 2009 ... All the individual weights were recorded and the connection weights and the overall connection weights for each input were calculated.

Alternatives:

  • aggregate connection weights
  • total connection weights
  • cumulative connection weights
  • sum of connection weights
  • average connection weights

Related Comparisons

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